SINS/ANS/GPS integration using Federated Kalman Filter based on optimized information-sharing coefficients

The elemental notion of the multisensor integrated navigation system is the utilization of a medium exactitude INS In conjunction with one or more auxiliary sensors which perform as error confining sources. The SINS/ANS/GPS integration is an operative way of providing an accurate and reliable system for midcourse navigation and guidance of medium and long range weapon systems. Contained by the INS, a Kalman filter is employed which accepts the auxiliary source inputs and provide a best estimate of the navigation information as well as estimates of the modeled error sources. This paper presents a theory and implementation of Federated Kalman Filter realized with an optimized information sharing algorithm, and designs the integrated navigation system. Using the proposed method, there is no upshot on the global optimality of the filter. Simulation results of the integrated navigation system for a ballistic missile application demonstrate the validity of this method on improving the navigation system's reliability, robustness and accuracy with the estimation and compensation for inertial sensors errors.